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Accurate attitude estimation under high accelerations and magnetic disturbances

机译:在高加速度和电磁干扰下的精确姿态估计

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Accurate attitude estimation in high dynamic motion scenarios like unmanned aerial vehicle navigation or human motion and magnetically disturbed indoor environments requires compensation of accelerometer disturbances as well as magnetometer disturbances. This paper proposes a novel algorithm for accelerometer disturbance rejection by adaptive estimation of accelerometer measurement covariance matrix online. Magnetic disturbances are generally lasting long compared to accelerometer disturbances which are generally short term in indoor navigation environments. Novel two step Kalman filter update method is proposed to separate attitude correction from heading correction. The magnetometer is used only for heading update such that the attitude estimation is not affected by errors in magnetometer measurement. Performances of the proposed algorithms are shown by using real world sensor data.
机译:在高动态运动场景中(例如无人机导航或人类运动以及室内受到电磁干扰的情况下),准确的姿态估计需要对加速度计干扰和磁力计干扰进行补偿。通过对加速度计测量协方差矩阵的在线自适应估计,提出了一种抑制加速度计干扰的新算法。与加速度计的干扰相比,电磁干扰通常会持续较长的时间,而加速度计的干扰在室内导航环境中通常是短期的。提出了一种新颖的两步卡尔曼滤波器更新方法,将姿态校正与航向校正分开。磁力计仅用于航向更新,以使姿态估计不受磁力计测量误差的影响。通过使用真实世界的传感器数据显示了所提出算法的性能。

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